Data Engineer

Sila • Seattle, WA

2d • $100,000 - $180,000 • Onsite

About The Position

As a Professional Services Consultant specializing in Data Engineering, you will play a critical role in designing, developing, and maintaining the data infrastructure and cloud platform that supports our clients’ business needs. The ideal candidate will be an experienced software engineer who has a passion for data management and is prepared to dive in as needed to help the application teams where needed. You will collaborate with data scientists, analysts, subject matter experts, and other stakeholders to ensure efficient data pipelines, reliable systems, and actionable insights, providing strategic advice on data management, data optimization, and data architecture. You will bring your strong analytical skills and ability to interpret data and provide actionable insights to the data platform team using exceptional communication and interpersonal skills, with the ability to build strong client relationships. Significant collaboration is required in this role, as is the ability to work independently in a fast-paced environment.
This candidate is preferred to be located in the Seattle Metropolitan area and may be expected to be in-person at our client locations up to 5 days a week.

Requirements

• Database Query: Experience building complex and efficient SQL queries to combine data from multiple sources and databases.
• Development: Bring proficiency in programming languages such as R, Python, or Java to build data ingestion scripts, data transformation scripts, and APIs to access data from source systems and provide the data to application layers.
• Data Pipeline Development: Design, develop, and maintain scalable and reliable pipelines in IBM DataStage to process and integrate data from various sources into centralized data warehouses or lakes; create data cleansing and transformation processes.
• Data Quality Assurance: Implement data validation, cleansing, and monitoring processes to ensure data integrity and accuracy; drive data quality reports.
• API Management: Proven experience in designing, building, and using robust APIs. The ideal candidate will play a key role in enabling seamless data integration across systems, ensuring scalable and secure access to data assets. A strong understanding of RESTful principles, authentication protocols, and best practices in API lifecycle management is essential to support both internal and external data consumers.
• Cloud Infrastructure: Deploy and manage cloud-based data storage and processing solutions, leveraging an AWS platform or other cloud providers such as Google or Azure.
• Documentation: Create and maintain clear documentation for data workflows, data models, systems, and processes; identify and document data sources and build interface control documents (ICDs) for APIs; develop deployment instructions for pipelines; develop user guides and training materials for developers to access APIs.
• Bachelor’s or Master’s degree in Computer Science, Engineering or related equivalent field.
• Minimum of 5 years of experience in data engineering or related roles.
• Experience working in SAFe/Agile teams.

Nice To Haves

• Database Management: Build, optimize, and manage database architectures, ensuring high availability, security, and performance. Understanding of relational, dimensional, and graph database theory.
• Data Modeling: Create logical and physical data models, apply schema design principles and set modeling standards for data platforms, data lakes or data mesh.
• Data Governance: Bring familiarity with data governance and compliance requirements such as GDPR, CCPA, etc. and application of governance policies and procedures; identify and document governance standards.
• Databricks
• Automation and Optimization: Identify and implement opportunities to streamline data workflows and improve processing efficiency; experience with containerization and orchestration tools is preferred.

Responsibilities

• Engage with Clients: Understand clients' business challenges and objectives, providing expert advice on data strategy and transformation.
• Collaboration: Work closely with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver solutions.
• Continuous Improvement: Keep up-to-date with the latest data management trends, emerging technologies, tools, and best practices to ensure continuous improvement and innovation, providing clients with cutting-edge solutions.
• Soft Skills: Strong problem-solving abilities, exceptional attention to detail, and the ability to communicate complex technical concepts effectively to both technical and business stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level